-------------------------------------------------------------------------------August, 7, 2017DESCRIPTION OF DATASETThis folder contains the replication files for the following paper:Bail, Christopher A. 2016. "Combining Network Analysis and Natural Language Processing to Examine how Advocacy Organizations Stimulate Conversation on Social Media." Proceedings of the National Academy of Sciences, 113:42 11823-11828These data describe the social media outreach of 82 autism and organ donation advocacy organizations on Facebook between 2011-2012 collected via a social media application that collected public and non-public data from the Facebook Application Programming Interface and surveyed representatives of the organization in order to obtain additional information on the size, resources, and tactics of the organization as it attempts to generate attention for its cause on  social media.Please cite these data using the citation listed above.ABSTRACT (of article)Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-ranging conversation among social media users, whereas the vast majority of them receive little or no attention. I argue that advocacy organizations are more likely to inspire comments from new social media audiences if they create �cultural bridges,� or produce messages that combine conversational themes within an advocacy field that are seldom discussed together. I use natural language processing, network analysis, and a social media application to analyze how cultural bridges shaped public discourse about autism spectrum disorders on Facebook over the course of 1.5 years, controlling for various characteristics of advocacy organizations, their social media audiences, and the broader social context in which they interact. I show that organizations that create substantial cultural bridges provoke 2.52 times more comments about their messages from new social media users than those that do not, controlling for these factors. This study thus offers a theory of cultural messaging and public deliberation and computational techniques for text analysis and application-based survey research.-------------------------------------------------------------------------------AUTHOR�S CONTACT INFORMATIONChristopher A. BailLowey Associate Professor of Sociology and Public Policy254 Soc./Psych HallDuke University417 Chapel Dr. Durham, NC 27708christopher.bail@duke.edu--------------------------------------------------------------------------------FILE DESCRIPTIONREADME.txt							This fileBail 2016 PNAS.Rdata			Main dataset R Data FrameBail 2016 PNAS.csv				Main dataset .csv--------------------------------------------------------------------------------DESCRIPTION OF VARIABLES"no_unique_comments_more_than_three_words"     The number of unique social media users who made comments about an advocacy organization�s posts that were more than three words long. Note: values of this indicator are binned to protect anonymity of organizations and results may therefore differ from main models presented in our article. Values are binned into increments of 5 (except values of 0 and 1), in order to prevent public identification organizations. "cultural_betweenness"The betweenness centrality of the organization by day created using natural language processing and weighted network analysis techniques described in main text of paper. "no_posts_previous_day"                               	The total number of posts produced by the organization during the previous day" org_budget"           	Organization�s total yearly budget, reported by organizational representative to study�s social media application survey. Note: values of this indicator are binned to protect anonymity of organizations and results may therefore differ from main models presented in our article1	>0			<1,000,0002	>1,000,000		<5,000,0003	>5,000,000		<10,000,0004	>10,000,000                "org_no_page_fans_day_of_post"                        	The organization�s Total number of Facebook fans (varies by day               "org_betweennes_centrality_daily_network"             	Betweenness centrality of organization in two mode network that links organizations and Facebook commenters across entire advocacy field by day."org_closeness_centrality_daily_network"        	Closeness centrality of organization in two mode network that links organizations and Facebook commenters across entire advocacy field by day.      "no_audio_visuals_org_posts_previous_day"         	Number of posts produced by organization that contain photos, videos, or music, during the previous day. "total_org_page_views_from_facebook_advertising"      	Total number of people who viewed an organization�s posts each day because the organization paid to advertise within the person�s Facebook news feed"total_org_page_views_day_of_post"       Total number of people who viewed organization�s posts each day                                    "no_page_views_east_us"              The total number of people who viewed the organization�s posts from the Eastern U.S. during the previous day.                 "no_page_views_midwest_us"       The total number of people who viewed the organization�s posts from the Midwestern U.S. during the previous day.                     "no_page_views_south_us"          The total number of people who viewed the organization�s posts from the Southern U.S. during the previous day.                    "no_page_views_west"  The total number of people who viewed the organization�s posts from the Western  U.S. during the previous day.                                "no_page_viewers_under_35_by_day"            The total number of people who viewed the organization�s posts who are under age 35 during the previous day.         "percent_female_page_viewers_by_day"         The percentage of people who viewed the organization�s posts who were female during previous day.         "number_of_org_blog_mentions_previous_day"   The total number of mentions the organization received during the previous day on Google Blogs.         "number_of_org_news_articles_previous_day"            The total number of mentions the organization received during the previous day on Google News"number_google_searches_about_issue_previous_day"     Relative volume of Google searches for term �autism� or �organ donation� during the previous day (depending upon sample, see below)